Case Western Reserve University

What you'll study

The programme builds a solid mathematical and computational foundation in probability, inference and data analysis, then applies those tools to problems in biology, medicine and public health. Core coursework typically includes calculus and linear algebra, introductory and intermediate probability and mathematical statistics, regression and multivariate methods, design of experiments and statistical computing (principally R and Python).

• Foundations: calculus sequence, linear algebra, discrete mathematics as appropriate, and an introduction to mathematical reasoning.
• Core statistics: probability theory, mathematical statistics, point and interval estimation, hypothesis testing, regression and ANOVA.
• Computing and data science: statistical programming, data wrangling, reproducible research, data visualisation and introduction to machine learning methods.
• Biostatistics-specialist topics: epidemiologic methods, survival analysis, longitudinal and correlated data analysis, generalized linear models, clinical trials design and analysis, and bioinformatics/statistical genomics electives.
• Applied experience: capstone project or senior thesis applying statistical methods to a real biomedical dataset, plus options for internships and supervised research with faculty in statistics, public health or medical school departments.

Entry requirements

Applicants should demonstrate strong preparation in mathematics and quantitative reasoning. Typical expectations include evidence of high achievement in high school mathematics (including precalculus and preferably calculus), and strong grades in related STEM courses. Admissions assessors also look for a clear interest in quantitative work and applied health or biological problems.

• High school diploma or equivalent with strong grades in mathematics.
• Preparation in calculus is strongly recommended; coursework or exams showing readiness for university-level calculus helps your application.
• Submission materials usually include a personal statement, academic transcripts, and one or more teacher recommendations; standardised test submission policies may vary, so follow the university’s current guidance.
• Transfer applicants should provide college transcripts and descriptions of completed quantitative coursework; prior calculus, linear algebra and introductory statistics courses strengthen a transfer application.

Career prospects

Graduates with a biostatistics emphasis are prepared for roles that require rigorous quantitative analysis of biological and health data. Common entry-level positions include junior biostatistician, data analyst or research assistant in environments such as pharmaceutical and biotech companies, contract research organisations, hospitals and public health agencies.

• Work in clinical trials design and analysis, regulatory submissions and drug development.
• Data science and analytics roles in healthcare systems, medical device firms and health-tech startups.
• Positions in public health, epidemiology units and government health agencies analysing surveillance and population health data.
• Many graduates pursue further study — master’s or doctoral programmes in biostatistics, statistics, epidemiology or related fields — or professional degrees in medicine or public health.

Why study at Case Western Reserve University

Case Western Reserve offers an interdisciplinary environment that is particularly well suited to training biostatisticians. The university’s proximity to major medical centres in Cleveland provides undergraduates with opportunities for applied projects, internships and collaborative research with clinicians and public health researchers.

• Cross-disciplinary collaboration: students can take electives and conduct research with faculty in the School of Medicine, public health programmes and biomedical engineering.
• Applied research opportunities: access to clinical and translational research settings, enabling practical experience in analysing real-world health data.
• Strong computational resources and support for undergraduate research, including capstone supervision and mentorship from faculty active in biostatistics and health data science.
• Career support through university career services and industry connections in the local biotech and healthcare community to help secure internships and entry-level positions.